Author Archives: Terence Yim

Terence Yim is a Software Engineer at Cask, responsible for designing and building realtime processing systems on Hadoop/HBase. Prior to Cask, Terence worked at both LinkedIn and Yahoo!, building high performance large scale distributed systems.

Apache Spark™ is a general data processing framework, which is getting popular due to its fast data model and its flexible execution engine compared to MapReduce. In fact, Spark is becoming an essential technology for data analytics and this has become even more evident by the fact that all the top three Hadoop distributions are … Read more

Java class loading is one of the most fundamental and powerful concepts provided by the Java Platform. Understanding the class loading mechanism helps you when designing and building extensible application frameworks. You can also avoid spending many hours in debugging exceptions such as ClassCastException and ClassNotFoundException, among others. In this post, we will talk about … Read more

A real time stream processing framework usually involves two fundamental constructs: processors and queues. A processor reads events from a queue, executes user code to process them, and optionally writing events to another queue for additional downstream processors to consume. Queues are provided and managed by the framework. Queues transfer data and act as a … Read more

Please note: Continuuity is now known as Cask, and Continuuity Reactor is now known as the Cask Data Application Platform (CDAP). Introducing Twill to the Hadoop community – Read first post of the Twill series Writing a distributed application using Twill – Read second post of the Twill series Apache Twill Incubator Page – Visit … Read more

Please note: Continuuity is now known as Cask, and Continuuity Reactor is now known as the Cask Data Application Platform (CDAP). Read first blog post of the Weave series In this second blog post of the Weave series, we would like to show you how writing a distributed application can be as simple as writing … Read more